For completeness, we report quantitative metrics available in classification literature, specifically Insertion, Deletion, and Pointing game. Deletion and Insertion, introduced in RISE [1]}, measure how well the saliency map captures true causes of model decision. Deletion sequentially removes pixels from the image (starting from the most salient) while measuring how quickly the model's output deviates from the original prediction. Insertion sequentially adds salient pixels starting from a completely empty image and measures how fast it approaches the target prediction. We adapt these metrics using the similarity score (Equation 4) and compute them for D-RISE with \((h, w)\)  resolutions set to \((30, 30)\)  for YOLOv3 (Table REF ).
